Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Yinsuo Zhang"'
Autor:
Jenelle White, Aaron A. Berg, Catherine Champagne, Yinsuo Zhang, Aston Chipanshi, Bahram Daneshfar
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 89, Iss , Pp 102092- (2020)
Satellite-derived vegetation indices are widely utilized in yield forecasting models; however, they can be heavily impacted by atmospheric conditions due to their reliance on visible and near-infrared portions of the electromagnetic spectrum. Given t
Externí odkaz:
https://doaj.org/article/3b3eb493c4f046388dd5ff02e019ddc6
Autor:
Jiangui Liu, Jiali Shang, Budong Qian, Ted Huffman, Yinsuo Zhang, Taifeng Dong, Qi Jing, Tim Martin
Publikováno v:
Remote Sensing, Vol 11, Iss 20, p 2419 (2019)
This study investigated the estimation of grain yields of three major annual crops in Ontario (corn, soybean, and winter wheat) using MODIS reflectance data extracted with a general cropland mask and crop-specific masks. Time-series two-band enhanced
Externí odkaz:
https://doaj.org/article/a7198f0ae1fc4d839a831907419c9405
Publikováno v:
Remote Sensing, Vol 6, Iss 10, Pp 10193-10214 (2014)
Crop yield forecasting plays a vital role in coping with the challenges of the impacts of climate change on agriculture. Improvements in the timeliness and accuracy of yield forecasting by incorporating near real-time remote sensing data and the use
Externí odkaz:
https://doaj.org/article/51a111c1e92641969f1c67fe507d6e19
Publikováno v:
Geosciences, Vol 8, Iss 4, p 127 (2018)
Satellite soil moisture is a critical variable for identifying susceptibility to hydroclimatic risks such as drought, dryness, and excess moisture. Satellite soil moisture data from the Soil Moisture Active/Passive (SMAP) mission was used to evaluate
Externí odkaz:
https://doaj.org/article/1830674f1727487da98ed7920dcd595f
Autor:
Taifeng Dong, Jiangui Liu, Jiali Shang, Budong Qian, Ted Huffman, Yinsuo Zhang, Catherine Champagne, Bahram Daneshfar
Publikováno v:
Remote Sensing, Vol 8, Iss 4, p 281 (2016)
Cropland productivity is impacted by climate. Knowledge on spatial-temporal patterns of the impacts at the regional scale is extremely important for improving crop management under limiting climatic factors. The aim of this study was to investigate t
Externí odkaz:
https://doaj.org/article/fc525aee1bb3435aadbc785e9d190ea2
Publikováno v:
International Journal of Climatology. 42:2351-2367
Publikováno v:
Agricultural and Forest Meteorology. 268:354-362
Canola production is primarily attributed to variations in precipitation and temperature, however the direct relationship between soil moisture and canola yield has yet to be fully evaluated. Recent advancements in microwave remote sensing offer the
Autor:
Aston Chipanshi, Andrew Davidson, Gordon Reichert, Catherine Champagne, Bahram Daneshfar, Frédéric Bédard, Lauren Koiter, Yinsuo Zhang
Publikováno v:
Remote Sensing Applications: Society and Environment. 13:121-137
Land cover maps are often required in Earth Observation (EO) data analysis to isolate regions where specific land classes are present. They are normally derived from remote sensing images and ground truthed inputs. The crop cover maps that target spe
Publikováno v:
Atmosphere-Ocean. 56:28-39
Interannual variations of spring wheat yields in Canadian agricultural regions are analyzed, together with the associated sea surface temperature (SST) anomalies in the northern hemisphere tropics and extratropics, from 1961 to 2015. The cubic trend
Autor:
Aaron A. Berg, Yinsuo Zhang, Aston Chipanshi, Bahram Daneshfar, Catherine Champagne, Jenelle White
Publikováno v:
International Journal of Applied Earth Observation and Geoinformation. 89:102092
Satellite-derived vegetation indices are widely utilized in yield forecasting models; however, they can be heavily impacted by atmospheric conditions due to their reliance on visible and near-infrared portions of the electromagnetic spectrum. Given t